Process optimization of extruded noodles from Cocoyam (Colocasia Esculenta) and Bambara groundnut (Vigna Subterranea) flour

Abstract

A noodle is a thin, long strip of spaghetti or a similar flour paste consumed with a sauce or taken with warm water with sugar and milk added as desired. In this regard, a modified noodle was produced from cocoyam with Bambara ground nut added to enhance the nutritional composition of the noodle. Central Composite Design (CCD) using Response Surface Methodology (RSM) was used in the optimization procedure. The aim was to develop the best mix of procedure variables that can give optimum formulation with a high protein. The process variables were feed composition (X1), barrel temperature (X2), and feed moisture composition (X3). The responses were moisture, protein, fat, and fiber. Regression models and residual plots were generated and adequacy was tested with regression coefficient (R2) and the lack of fit test. Results of the analysis of variance (ANOVA) indicated that the process variables had a significant effect on the protein (p < 0.05). Results for regression coefficients prove a fair fit of the model. The optimum noodle had 60g of Bambara ground nut, 120 oC barrel temperature, and 16% moisture content. Its responses were 10.66 mg/100g protein, 0.95 mg/100g fat, 1.60 mg/100g ash, and 1.75 mg/100g fiber. The optimized recipe shows improve nutrients.